%0 Generic %1 Carolin2023 %A Wienrich, Carolin %A Carolus, Astrid %A Markus, André %A Augustin, Yannik %A Pfister, Jan %A Hotho, A. %D 2023 %J Comput. %K Friendship HumanAIInteraction SocialPerception Technology UserExperience VoiceAssistants edited_with_chatgpt posted_with_chatgpt %P 77 %R 10.3390/computers12040077 %T Long-Term Effects of Perceived Friendship with Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions %U https://www.semanticscholar.org/paper/176b3f7a02f1922e6d81c5db07535ab7d8227524 %V 12 %X Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.

@JournalArticle{Carolin2023, abstract = {Social patterns and roles can develop when users talk to intelligent voice assistants (IVAs) daily. The current study investigates whether users assign different roles to devices and how this affects their usage behavior, user experience, and social perceptions. Since social roles take time to establish, we equipped 106 participants with Alexa or Google assistants and some smart home devices and observed their interactions for nine months. We analyzed diverse subjective (questionnaire) and objective data (interaction data). By combining social science and data science analyses, we identified two distinct clusters—users who assigned a friendship role to IVAs over time and users who did not. Interestingly, these clusters exhibited significant differences in their usage behavior, user experience, and social perceptions of the devices. For example, participants who assigned a role to IVAs attributed more friendship to them used them more frequently, reported more enjoyment during interactions, and perceived more empathy for IVAs. In addition, these users had distinct personal requirements, for example, they reported more loneliness. This study provides valuable insights into the role-specific effects and consequences of voice assistants. Recent developments in conversational language models such as ChatGPT suggest that the findings of this study could make an important contribution to the design of dialogic human–AI interactions.}, added-at = {2024-01-10T17:56:14.000+0100}, author = {Wienrich, Carolin and Carolus, Astrid and Markus, André and Augustin, Yannik and Pfister, Jan and Hotho, A.}, biburl = {https://www.bibsonomy.org/bibtex/2c45f63872d6b0fcd22781cbe6461c462/chiir_demo}, day = 13, description = {This paper explores the long-term effects of perceived friendship with intelligent voice assistants (IVAs) on user behavior, experience, and social perceptions. Over nine months, 106 participants interacted with Alexa or Google assistants, revealing distinct clusters of users based on their social roles assigned to IVAs. These roles significantly influenced their interaction frequency, enjoyment, and empathy towards IVAs. The study combines social science and data science, providing valuable insights for designing dialogic human–AI interactions.}, doi = {10.3390/computers12040077}, interhash = {0d2e4ea36c41a345be1b9b01eedbc179}, intrahash = {c45f63872d6b0fcd22781cbe6461c462}, journal = {Comput.}, keywords = {Friendship HumanAIInteraction SocialPerception Technology UserExperience VoiceAssistants edited_with_chatgpt posted_with_chatgpt}, month = {4}, pages = 77, timestamp = {2024-01-10T17:59:30.000+0100}, title = {Long-Term Effects of Perceived Friendship with Intelligent Voice Assistants on Usage Behavior, User Experience, and Social Perceptions}, url = {https://www.semanticscholar.org/paper/176b3f7a02f1922e6d81c5db07535ab7d8227524}, volume = 12, year = 2023 }